Verify images with Zapier and Peltarion
Build an automated and effective system that verifies customer photo uploads.
Put yourself in the shoes of a car insurer. They receive a lot of insurance claims from their customers, and the insurer must ensure that every customer’s car is in fact damaged before paying any money. This is a tedious task but luckily a task that can be automated.
In this tutorial, we’ll show you how to set up a verification system that uses the customer’s information and image and then notifies systems administrators when something is wrong.
- Target audience: Intermediate users
- Estimated time: 15 minutes
You will learn
- Build a Zapier workflow
- Connect Peltarion to a Zapier workflow
Create a spreadsheet with insurance claims
Make your own copy of this spreadsheet with insurance claims that we’ve made. The spreadsheet includes information on each claim. Most importantly, it contains a link to a photo for each claim. You will use that photo in a Peltarion classification model.
Tips on tools for survey collection
You can also create your own spreadsheet that includes a photo for each claim. This photo must have a link so the Peltarion classification model can use it.
We used Typeform to set up a form that, from a chatwindow, collected dummy-information about insurance claims from customers. You could also try AirTable, which also worked very well and, as an added benefit, also removes the need for a spreadsheet in the step below.
Create Zapier flow: Peltarion ←→ Google Sheet
Now let’s set up a flow in Zapier to call the Peltarion model and receive an email notification if the photo can’t be verified.
This is the Zapier flow that you’re going to create:
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Log in to Zapier.
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In the My apps window add a Peltarion connection.
If the Peltarion connection is not in the list, search for "Peltarion".
We’ve pre-trained demo model already. Use the URL and Token below to access our deployed model. You can also build and deploy a car classifier yourself in our car damage classifier tutorial.-
Token: 1a3ddc3d-f17a-4a3d-aeb8-c73c4d08925f
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In the Zaps window make a Zap.
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The first trigger is New Spreadsheet Row in Google Sheets.
Make sure it triggers whenever a new row is added to your spreadsheet (the one you created in the previous part of the tutorial). -
Add action Prediction in Peltarion.
In the next step of the Zapier flow, call a Peltarion model trained to classify different types of car damage (ours or your own) . -
Add filter Only continue if… step to sort out the photos where the Peltarion model isn’t confident in its prediction.
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Add a Helper app Filter
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In Filter Setup & Testing click Only continue if… and select Predictions by Peltarion and then Class confidence.
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Choose condition (Number) Less than…
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Enter value 1 in the last field.
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Press Continue to find out if your prediction would have passed.
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Add step that send you and email if a photo couldn’t be verified.
Search for Email by Zapier and add it (will then show as Action / Send Outbound Email). Enter this info:-
To:
<your mail> -
Subject: Unverified insurance claim
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Body: Click in the Body field
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Select Insert data → New Spreadsheet Row in Google sheets → Photo
This will add a link to the unverified image to the mail. -
Then add some text like is unverified. Please take a look.
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Done!
Verify zap - Recieve a mail from the zap
To verify copy the row below and paste it into you spreadsheet:
Charlie |
https://storage.googleapis.com/bucket-8732/Zapier_car_damage_images/CardamageTest.jpg |
unknown |
Example:
Recap
And that’s it! Your customized verification system is finished. In this tutorial, you learned to:
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Build a workflow using apps you already use.
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Deploy a Peltarion model in Zapier.
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Integrate it into your processes.
Next project
If you’re keen to try out another one of our tutorials that utilize another low-code tool, check out the Sales forecasting tutorial and its integration with Google Sheets and with Microsoft Excel.